{"id":"W2060609167","doi":"10.1109/glocomw.2013.6855701","title":"Dynamic access class barring for M2M communications in LTE networks","year":2013,"lang":"en","type":"article","venue":"","topic":"IoT Networks and Protocols","field":"Engineering","cited_by":129,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"EnodeB; Computer science; Heuristic; Computer network; Base station; Network packet; User equipment; LTE Advanced; Class (philosophy); Random access; Radio access network; Factor (programming language); Access network; Telecommunications link","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008660318,0.0005056638,0.0005827831,0.0007802017,0.001295249,0.001204095,0.001162352,0.0005518884,0.000798343],"category_scores_gemma":[0.003494374,0.0003276733,0.0003131223,0.0006474618,0.0009207043,0.0009891,0.0007783978,0.0007622303,0.000118756],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001942963,"about_ca_system_score_gemma":0.001988752,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01290599,"about_ca_topic_score_gemma":0.01809729,"domain_scores_codex":[0.9994094,0.0001847633,0.00001860774,0.00007042917,0.0001328651,0.0001839451],"domain_scores_gemma":[0.9982343,0.001148762,0.0002681122,0.0001411322,0.0001000817,0.0001076209],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003061448,0.00009338314,0.001846613,0.00008868292,0.00003249139,0.0002478742,0.000151482,0.8993143,0.01266659,0.03105325,0.001769422,0.05242981],"study_design_scores_gemma":[0.000009559713,0.00004579285,0.0003175512,0.000007554924,0.00000992685,0.00006520841,0.00003315549,0.9921632,0.001721779,0.004879736,0.0007313551,0.00001513112],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1208975,0.001500688,0.8709209,0.0003593036,0.00005898331,0.00009871235,0.00007465723,0.0006141433,0.005475204],"genre_scores_gemma":[0.9794528,0.0001713748,0.01990651,0.00003389763,0.00001662828,0.00003296603,0.00001669422,0.00001440214,0.0003546817],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01290599,"threshold_uncertainty_score":0.02566171,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02592043185137003,"score_gpt":0.3087231719541647,"score_spread":0.2828027401027947,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}